(3) Single: The context vector is obtained by the attention mechanism proposed by [1]}. This attention mechanism gives the best performance with the word-level decoding model.
\(&\mathbf {u}_t^i = \mathbf {W}_{u} \mathbf {h}_i^E \nonumber \\&\mathbf {q}_t^i = \mathbf {W}_{q} \mathbf {h}_{t-1}^D + \mathbf {b}_{q} \nonumber \\&\textnormal {a}_t^i = \mathbf {v}_a \tanh (\mathbf {q}_t^i + \mathbf {u}_t^i) \nonumber \\&\alpha _t = \mathrm {softmax(\mathbf {a}_t)} \nonumber \\&\mathbf {e}_t = \sum _{i=1}^n \alpha _t^i \mathbf {h}_i^E\) 
